Google Earth and its related products Google Sky, Google Moon, etc. are incredible tools for real work as well as hours of endless amusement. Unfortunately, the shear amount of imaging data that went into them made it impossible for a human being to check that the combined images were actually correct in all cases. My main field in astronomy is imaging and for every imaging project I have done, from the Hubble Ultra Deep Field to the study of the cores of nearby galaxies, a painstaking pixel-by-pixel inspection of the images has been essential. When you look for rare objects at very high redshift there is little room for error and an image artifact can easily ruin your day and perhaps your reputation. Despite this careful checking of the results of computer processing, I have had my share of objects that have disappeared once better data were obtained. One can never be too careful.

The number of errors in Google Earth is amazingly small but not zero. Any automated imaging combination of heterogeneous data is bound to occasionally fail and produce some non-sense that is immediately recognizable as such by a trained eye. Years ago we had the report of a mysterious island in the Pacific discovered on Google Earth. I checked it out and it didn’t take more than a second to see that it was an image artifact, probably the result of two separate images that had not been appropriately matched or perhaps due to insufficient coverage in that area. The give away was the very dark color and the unphysically sharp boundary. Every imaging system has a finite resolution and if you see something that appears much sharper than other objects in its neighborhood then it is very likely an artifact. So it was for the mysterious island that – as the media reported some time later – “disappeared” in a later version of Google Earth data.

Recently, I came across a report and a video of “alien bases” found on the Moon using Google Moon. I was virtually sure that there were no alien bases there but still decided to check it out. In fact, as soon as the video starts you can see that in the pole-on view of the Moon there is an area that looks like a stripe: it is where imaging data of different quality are mixed and matched (Figure 1). The edges between different data are very unreliable. In this type of situation in a science project one would simply disregard those areas and their immediately surrounding portions of the image. Unfortunately, UFO aficionados are not so easily deterred. Zooming in on the edge between the two types of data they found lots of “alien bases”: most are elongated, very sharp, structures, much sharper in fact than the crater contours visible next to them. One “base” is in fact close to half a crater, a crater that is visible only for half of its circumference, with the other half crater being found in a lower quality lunar image. Clearly all those suspicious features are artifacts and any other interpretation is non-sense.

People are spending time looking at science data. It is in everybody’s interest to make their efforts useful for the progress of science. By combining carefully chosen problems, training sets, and redundancy, a citizen science experiment can reduce the margin for errors and lead to very interesting results. For example, Planet Hunters (www.planethunters.org), a recent citizen science project based on Kepler Space Telescope data, was able to identify a very peculiar star that seems to be surrounded by a lot of large debris, perhaps comets or remnants of a planetary collision. These results have led to a scientific publication (Boyajian et al. 2015, submitted to MNRAS and arxiv.org:1509.03622, also mentioned on the Atlantic in an article by Ross Andersen). Another very successful citizen science project has been Galaxy Zoo (www.galaxyzoo.org) that has led to 48 science papers. Circumstellar disks are the target of the NASA-funded citizen project is Disk Detective (www.diskdetective.org), with the goal of identifying in the WISE data stars that may host or may be forming extrasolar planets. Citizen science has the potential to engage many more people than it does today and tap on a large reservoir of talent available in the public. If we succeed in doing so we will have better science and perhaps fewer non-sensical news reports.

Figure 1. When loading the Moon in Google Earth the stripe with data-matching issues is immediately visible. Along the edges of that stripe finding artifacts is very easy (Image credit: Google Earth).

This Month’s Featured Author

Dr. Brian Williams received his B.S. from Florida State University in 2004 and his Ph.D. from North Carolina State University in 2010. He was a NASA Postdoctoral Fellow at NASA Goddard Space Flight Center for three years, after which he worked as a research scientist at NASA GSFC with Universities Space Research Association. He arrived at STScI in February of 2017, and is currently a Support Scientist in the Science Mission Office. His research interests include supernovae and supernova remnants, shock physics and particle acceleration, and dust in the interstellar medium.